Optimising a multi-strategy implementation intervention to improve the delivery of a school physical activity policy at scale: findings from a randomised noninferiority trial
Bibliographic record
Abstract
BACKGROUND: To maximise their potential health benefits, school-based physical activity policies need to be implemented at scale. This paper describes the third in a sequence of trials that sought to optimise an effective strategy (PACE) to assist schools' implementation of a physical activity policy. Specifically, it aimed to determine the probability that a multi-strategy intervention adapted to reduce in-person contact (Adapted PACE) was "as good as" the original intervention (PACE) in increasing the weekly minutes of structured physical activity implemented by classroom teachers. METHODS: A noninferiority cluster randomised controlled trial was undertaken with 48 primary schools in New South Wales, Australia. Schools were randomised to receive PACE or a model with adaptations made to the delivery modes (Adapted PACE). Teachers' scheduled minutes of weekly physical activity was assessed at baseline (Oct 2018-Feb 2019) and 12-month follow-up (Oct-Dec 2019). The noninferiority margin was set at - 16.4 minutes based on previous data and decision panel consensus. A linear mixed model analysed within a Bayesian framework was used to explore noninferiority between the two PACE models. A cost minimisation analysis was conducted from the health service provider perspective, using the Australian dollar (AUD). RESULTS: The posterior estimate for the between group difference at follow-up was - 2.3 minutes (95% credible interval = - 18.02, 14.45 minutes). There was an estimated 96% probability of Adapted PACE being considered noninferior (only 4% of the posterior samples crossed the noninferiority margin of - 16.4 minutes). That is, the minutes of physical activity implemented by teachers at Adapted PACE schools was not meaningfully less than the minutes of physical activity implemented by teachers at PACE schools. The mean total cost was AUD$25,375 (95% uncertainty interval = $21,499, $29,106) for PACE and AUD$16,421 (95% uncertainty interval = $13,974, $19,656) for Adapted PACE; an estimated reduction of AUD$373 (95% uncertainty interval = $173, $560) per school. CONCLUSIONS: It is highly probable that Adapted PACE is noninferior to the original model. It is a cost-efficient alternative also likely to be a more suitable approach to supporting large scale implementation of school physical activity policies. TRIAL REGISTRATION: Retrospectively registered with the Australian New Zealand Clinical Trials Registry (ACTRN12619001229167).
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.025 | 0.057 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.004 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".